Signaling Pathway Dynamics
Signal transduction pathways, as the name implies, are often thought of as chains of molecules that simply relay external signals to end effectors. However, this is a misnomer because signaling pathways execute other important functions (e.g. signal amplification, signal processing, etc.) and can implement critical systems features (e.g. robustness, sensitivity, memory, etc.). Understanding such properties is crucial to understanding the biology of signaling pathways and they are best studied through signal pathway dynamics. We are interested in how dynamic input and output, such as oscillatory, pulsatile, and switch-like behavior, relates to topology, function, and regulation especially in the NF-kappaB, MAPK, and calcineurin pathways. Experimentally, we probe these pathways through a combination of live cell imaging, immunocytochemistry, Western blots, real time PCR, and other techniques. The resulting data is analyzed in the context of computational models of the pathway. In parallel, we are developing mathematical theory that can be used to evaluate pathway dynamics and system properties.
Gradient sensing by cells involves the ability to sense extremely small spatiotemporal differences in chemical or physical cues in a precise manner. Cells respond to external chemical gradients by polarizing and migrating toward chemoattractants or away from chemorepellants (chemotaxis) or undergoing directed morphogenesis (chemotropism). These phenomena are crucial for proper functioning of single-cell organisms, such as bacteria, amoebae and yeast; as well as multi-cellular systems as complex as the immune and nervous systems. Chemotaxis is also important in wound healing and tumor metastasis. In addition, the migratory behavior as well as morphogenetic growth of most of the cells in the body depends on the properties of the extracellular matrix. Mechanotransduction induced cues are important for phenomena like durotaxis (cell motility or growth up or down a rigidity gradient) and haptotaxis (up or down a gradient of cellular adhesion sites).
Traditionally, gradient sensing studies have been affected by lack of appropriate control of spatial (the actual shape of the gradient) or temporal gradients (gradient stability). Our lab has been developing a range of novel microfluidic device designs, which are tailor-made to allow accurately controlled gradient sensing studies for different cell-types. In addition, these studies are complemented by molecular biology approaches and mathematical modeling of the signal transduction pathways to understand the underlying basis of gradient sensing in these cells.
We study a diverse range of gradient sensing systems, ranging from pheromone sensing in yeast and axon guidance in embryonic Xenopus spinal neurons to the mammalian gradient sensing pathways involved in angiogenesis, tumor metastasis, haptotaxis and durotaxis.
We attempt to deepen the understanding of how bacteria interact with the host system in the context of infection. Bacterial pathogens make use of several strategies such as adhesions to host cells, cellular invasion followed by intracellular proliferation, adaptation, or persistence. To investigate these exquisite strategies of bacterial pathogens, we implement the precise control of chemical and mechanical cues on the microfluidic design for bacteria culture and bacteria-host co-culture environment. High throughput approaches using this microfluidic platform allow us to overcome the drawbacks of the traditional drug screening and experimentation with cells in suspension or on gel plates. Using quantitatively characterized cellular and molecular events based on the experiment approaches, we take into account various interactions, including those relying on various feedback loops and associated adaptive behavior, between bacterial pathogens and host systems.
Differentiation of Stem Cells
The process by which stem cells differentiate into various tissues is largely unknown due to the enormous complexity of signals, both chemical and mechanical. To add to this complexity, these signals change quickly overtime and are finely controlled by dosage. Current methods in cell culture conditions do not easily afford such fine control of the developing stem cells which results in experiments that are both time-consuming and expensive. To overcome these difficulties, our group is exploring the use of microfluidic devices and nanotechnology to finely control the chemical and physical environment of embryonic and mesenchymal stem cells. Currently these methods are being applied to understand the effect of various soluble factors such as Leukemia Inhibitory Factor (LIF) and Bone Morphogenic Protein 4 (BMP4) on self-renewing cells. Additionally, this group is exploring the soluble factors that affect the choice of stem cells to differentiate into the various germ layers, especially neuroectoderm or mesoderm. From these germ layers, cells such as neurons or cardiomyocytes can be derived which could have potentially dramatic clinical applications.
Control of Cell Shape & Polarity
Cells have the inherent ability to dynamically respond to changes in the extracellular environment. They change shapes to better adapt to environmental cues so they can carry out their tasks with efficiency. These cell shape changes are the result of dynamic reorganization of cytoskeleton proteins such as actin and microtubule regulated by a number of signaling molecules embedded in them. We are studying the molecular basis of cell shape changes in response to extracellular stimuli (chemical or mechanical in nature) in different model systems such as baker’s yeast and mammalian cells. In our experimental approaches we are using a variety of tools to study more efficiently the underlying cell biology that leads to cell shape change. For example, in addition to standard biochemical, molecular and microscopy techniques we are using microfluidics and bioengineering tools to mimic in-vivo extracellular stimuli in in-vitro cell culture system. Fluorescent protein tracking and detection is widely employed as reporter for gene expression in our studies. We also develop methods for quantitative examination of dynamic fluorescent protein expression and localization in living cells. For understanding gene function we are employing PCR-mediated gene disruptions to create either null or mutated alleles.
Heterotypic Cell Interaction
Cell behavior and functions are affected by its environment, which includes neighboring cells. This effect can be done by contact or by secreting soluble molecules. We investigate angiogenesis and tumor metastasis by studying interaction between tumor cells and endothelial cells for a wide range of scales: from single cell, to a group of cells to colonies. We are also interested in interactions between neuron and muscle cells, stem cell and differentiated cells, etc.
Biological networks are graphical representations of complex systems and processes, such as gene regulation, metabolism, or signal transduction. Large-scale topological analysis of these networks has revealed that they are not randomly organized. The intricate relations between their structure, function and dynamics need to be further investigated.
We study the dependence and interplay between network topology and the dynamics of the biological processes within a cell. We investigate ways in which network topology may have evolved to optimize the robustness of network dynamics. In addition, we investigate the notion of a close interplay between different kinds of biological networks: Specifically, we analyze how they interact as the cell receives and processes information about changes in its environment, and responds to them in optimal ways. To this end, we extensively study both the large-scale topology of biological networks and the function and dynamics of smaller topological motifs within them.
In our studies, we apply mathematical models, sophisticated simulation and visualization techniques, as well as our knowledge of the biochemical principles underlying network function. Our experimental facilities and resources permit us to change a cell’s environment in a controlled way, thus targeting different regions within the underlying biological network. By observing both single cells and in cell colonies, we can analyze diverse aspects of network dynamics.